What you'll learn
- Building Neural Networks with Tensorflow
Requirements
- You should know Python programming, have basic math knowledge, and basic concepts of machine learning before enrolling.
Description
You're going to learn the most popular library to build networks and machine learning algorithms.
In this hands-on, practical course, you will be working your way through with Python, Tensorflow, and Jupyter notebooks.
What you will learn:
Basics of Tensorflow
Artificial Neurons
Feed Forward Neural Networks
Activations and Softmax Output
Gradient Descent
Backpropagation
Loss Function
MSE
Model Optimization
Cross-Entropy
Linear Regression
Logistic Regression
Convolutional Neural Networks (with examples)
Text and Sequence Data
Recurrent Neural Networks (with examples)
Neural Style Transfer (in progress)
Who this course is for:
- You want to get into machine learning and artificial neural networks
- You already work in ML/AI and need to learn Tensorflow
- You are a student, know some coding, and want to get into machine learning
Instructor
![Cristi Zot](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.4 Instructor Rating
- 2,898 Reviews
- 143,109 Students
- 8 Courses
I’m Cristi. I hold an MS in Civil Engineering and I work as a Cybersecurity Analyst. I've got my Offensive Certified Security Professional Certification a couple of months ago.
Machine learning and AI are currently on my high interests as well and I am looking to combine ML/AI with cybersecurity at some point in the future.